Vehicle control method and apparatus

ABSTRACT

In a vehicle control apparatus, a gradient calculator calculates a gradient difference between a reference gradient of a reference road section of an own vehicle and a target gradient of an objective road section of an image-detected object. A corrector corrects, based on the calculated gradient difference, second location information about the image-detected object measured by an imaging device to thereby correct a second distance of the image-detected object relative to the own vehicle. A determiner determines whether a radar-based object is identical with the image-detected object in accordance with first location information about the image-detected object measured by a radar device and the corrected second location information about the image-detected object.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is based on and claims the benefit of priority fromJapanese Patent Application 2017-127329 filed on Jun. 29, 2017, thedisclosure of which is incorporated in its entirety herein by reference.

TECHNICAL FIELD

The present disclosure relates to vehicle control methods andapparatuses applicable for a vehicle including a radar device and animaging device.

BACKGROUND

Some vehicle control apparatuses use a fusion technology. The fusiontechnology checks a radar-based position, i.e. a radar-detectedposition, of an object detected by a radar device against an image-basedposition, i.e. an image-detected position, of an object detected by animaging device to thereby determine whether the radar-based position andthe image-based position are based on the same object. The fusiontechnology performs a fusion task to fuse, i.e. combine, the radar-basedposition and the image-based position to thereby generate a new fusionposition of the same object upon determining that the radar-basedposition and the image-based position are based on the same object.

For example, an object detection apparatus disclosed in Japanese PatentApplication Publication No. 2014-122873, which will be referred to asPTL, determines whether a radar-based position and an image-basedposition have a predetermined positional relationship therebetween. Theobject detection apparatus determines that the radar-based position andthe image-based position are based on the same object upon determiningthat the radar-based position and the image-based position have thepredetermined positional relationship therebetween. This therefore makesit possible for the vehicle detection apparatus to perform the fusiontask set forth above.

Note that each of a radar-based position and an image-based position isdetected as a position on a relative coordinate system having

(1) The center of the front of an own vehicle as its origin

(2) The width direction of the own vehicle passing through the origin asits X axis

(3) The travelling direction of the own vehicle passing through theorigin as its Y axis

That is, the object detection apparatus disclosed in the PTL specifieseach of the radar-based position and an image-based position based on

(1) A distance between the own vehicle and a corresponding object on therelative coordinate system

(2) A horizontal azimuth of a corresponding object with respect to theown vehicle on the relative coordinate system.

SUMMARY

The object detection apparatus disclosed in the PTL is configured tocalculate the distance between the own vehicle and an object based onthe position of the object with respect to the top-bottom direction,i.e. the vertical direction, in an image captured by the imaging device.

Unfortunately, the object detection apparatus cannot obtain the gradientor inclination of a reference road section on which the own vehicle istravelling and the gradient or inclination of an objective road section,which is different from the reference road section, on which the objectis located. For this reason, the object detection apparatus may resultin the calculated distance between the own vehicle and the objectincluding an error if there is a relative difference between thegradient of the reference road section and the gradient of the objectiveroad section.

This may result in difficulty for the object detection apparatus toaccurately determine whether the radar-based position and theimage-based position are based on the same object. This may thereforemake it difficult for the object detection apparatus to accuratelyperform the fusion task.

From this viewpoint, the present disclosure seeks to provide vehiclecontrol methods and apparatuses each installable in an own vehicle fordetecting target objects around the own vehicle. Each of the vehiclecontrol methods and apparatuses is capable of accurately determiningwhether a radar-detected object is identical with an image-detectedobject even if there is a relative difference between the gradient of areference road section on which the own vehicle is travelling and thegradient of an objective road section on which the image-based object islocated.

According to a first exemplary aspect of the present disclosure, thereis provided an apparatus for controlling an own vehicle that istravelling on a reference road section, the own vehicle including aradar device and an imaging device that are each configured to perform atarget-object detection operation. The apparatus includes a firstobtainer configured to obtain first location information about aradar-detected object in accordance with a result of the target-objectdetection operation performed by the radar device. The first locationinformation includes a first distance of the radar-detected objectrelative to the own vehicle and a first azimuth of the radar-detectedobject relative to the own vehicle. The apparatus includes a secondobtainer configured to obtain second location information about animage-detected object located on an objective road section based on aresult of the target-object detection operation performed by the imagingdevice. The second location information includes a second distance ofthe image-detected object relative to the own vehicle and a secondazimuth of the image-detected object relative to the own vehicle. Theapparatus includes a gradient calculator configured to calculate agradient difference between a reference gradient of the reference roadsection and a target gradient of the objective road section. Theapparatus includes a corrector configured to correct, based on thecalculated gradient difference, the second location information aboutthe image-detected object to thereby correct the second distance of theimage-detected object relative to the own vehicle. The apparatusincludes a determiner configured to determine whether the radar-detectedobject is identical with the image-detected object in accordance withthe first location information about the radar-detected object and thecorrected second location information about the image-detected object.

According to a second exemplary aspect of the present disclosure, thereis provided a method of controlling, using a computer, an own vehiclethat is travelling on a reference road section, the own vehicleincluding a radar device and an imaging device that are each configuredto perform a target-object detection operation. The method is configuredto cause the computer to execute the steps of

1. Obtaining first location information about a radar-detected object inaccordance with a result of the target-object detection operationperformed by the radar device, the first location information includinga first distance of the radar-detected object relative to the ownvehicle and a first azimuth of the radar-detected object relative to theown vehicle

2. Obtaining second location information about an image-detected objectlocated on an objective road section based on a result of thetarget-object detection operation performed by the imaging device, thesecond location information including a second distance of theimage-detected object relative to the own vehicle and a second azimuthof the image-detected object relative to the own vehicle

3. Calculating a gradient difference between a reference gradient of thereference road section and a target gradient of the objective roadsection

4. Correcting, based on the calculated gradient difference, the secondlocation information about the image-detected object to thereby correctthe second distance of the image-detected object relative to the ownvehicle

5. Determining whether the radar-detected object is identical with theimage-detected object in accordance with the first location informationabout the radar-detected object and the corrected second locationinformation about the image-detected object

Each of the apparatus and method is configured to calculate the gradientdifference between the reference gradient of the reference road sectionand the target gradient of the objective road section, and correct,based on the calculated gradient difference, the second locationinformation about the image-detected object to thereby correct thesecond distance of the image-detected object relative to the ownvehicle. Then, each of the apparatus and method is configured todetermine whether the radar-detected object is identical with theimage-detected object in accordance with the first location informationabout the radar-detected object and the corrected second locationinformation about the image-detected object.

This configuration enables the corrected second location informationwhich has been corrected using the gradient difference to be obtained,making it possible to accurately determine whether the radar-detectedobject is identical with the image-detected object. That is, thisconfiguration enables a fusion target object to be accurately obtainedeven if a gradient difference exists between the reference road sectionon which the own vehicle is travelling and the objective road section onwhich the image-detected object is located.

BRIEF DESCRIPTION OF THE DRAWINGS

Other aspects of the present disclosure will become apparent from thefollowing description of embodiments with reference to the accompanyingdrawings in which:

FIG. 1 is a block diagram schematically illustrating an example of theconfiguration of a vehicle control apparatus according to a presentembodiment of the present disclosure;

FIG. 2 is a diagram schematically illustrating a radar detection pointand an image detection point on a relative coordinate system accordingto the present embodiment;

FIG. 3 is a diagram schematically illustrating a collision predictionregion defined relative to an own vehicle according to the presentembodiment;

FIG. 4 is a diagram schematically illustrating a situation where animaging device captures a preceding vehicle that is travelling on anobjective road section having an upward gradient;

FIG. 5 is a diagram schematically illustrating how to correct an imagesearch region upon a gradient difference being positive according to thepresent embodiment;

FIG. 6A is a diagram schematically illustrating a position of the centerof a lower end of a preceding vehicle in a captured image in itsvertical direction;

FIG. 6B is a graph schematically illustrating a relationship between acorrection amount, the gradient difference, and the position of thecenter of the lower end of the preceding vehicle in the captured imagein its vertical direction upon the gradient difference being positive;

FIG. 7 is a diagram schematically illustrating how to correct the imagesearch region upon the gradient difference being negative according tothe present embodiment;

FIG. 8 is a graph schematically illustrating a relationship between acorrection amount, the gradient difference, and the position of thecenter of the lower end of the preceding vehicle in the captured imagein its vertical direction upon the gradient difference being negative;

FIG. 9 is a flowchart schematically illustrating a fusion determinationroutine carried out by an ECU illustrated in FIG. 1;

FIG. 10A is a flowchart schematically illustrating a subroutine of theoperation in step S19 of the fusion determination routine illustrated inFIG. 9; and

FIG. 10B is a flowchart schematically illustrating a modification of theoperation in step S20 of the fusion determination routine illustrated inFIG. 9.

DETAILED DESCRIPTION OF EMBODIMENT

The following describes a present embodiment of the present disclosurewith reference to the accompanying drawings.

FIG. 1 schematically illustrates a pre-crash safety (PCS) system 100based on a vehicle control apparatus according to the present embodimentinstalled in an own vehicle 50. The PCS system 100 is capable of

1. Recognizing an object located around the own vehicle 50, such asahead of the own vehicle 50 in the travelling direction of the ownvehicle 50, i.e. in the forward direction of the own vehicle 50

2. Performing control tasks of the own vehicle 50 including a collisionavoidance operation to avoid collision between the recognized object andthe own vehicle 50 and/or a damage mitigation operation to mitigatedamage due to collision therebetween upon determining that there is apossibility of the own vehicle 50 colliding with the recognized object

Referring to FIG. 1, the PCS system 100 includes an electronic controlunit (ECU) 10, a radar device 21, an imaging device 22, which are anexample of object detection sensors, a navigation system 23, and cruiseassist devices 30.

In FIG. 1, the ECU 10 serves as the vehicle control apparatus accordingto the present embodiment.

The radar and imaging devices 21 and 22 are communicably connected tothe ECU 10.

For example, the radar device 21 is designed to detect objects locatedin front of the own vehicle 50 using, for example, directionalelectromagnetic waves, i.e. probe waves, such as millimeter waves orradar waves. The radar device 21 is mounted at, for example, the centerof the front end of the own vehicle 50 such that its optical axis of theprobe waves is directed toward the forward direction of the own vehicle50.

The radar device 21 has a predetermined detection range that has apredetermined view angle, such as a detection angle, or scanning angle,and extends in the right and left direction around the optical axis.That is, the radar device 21 is capable of detecting the position of anobject within the detection range.

Specifically, the radar device 21 performs, in a first period, an objectinformation obtaining task to

1. Transmit probe waves to the detection range through a transmittingantenna

2. Receive reflected waves, i.e. echoes, based on reflection of thetransmitted radar waves by the outer surface of an object throughrespective receiving antennas

3. Calculate the relative position of the object relative to the ownvehicle 50 based on the transmission time of the probe waves and thereception times of the respective reflected waves

4. Calculate the azimuth of the object based on the differences in phasebetween the reflection waves received by the respective receivingantennas

5. Calculate the relative speed between the own vehicle 50 and theobject based on the frequencies of the reflected waves; the frequencieshaving been changed based on the Doppler effect.

That is, the radar device 21 obtains, in the first period, firstdetection information including the relative position, azimuth, andrelative speed of the object. Note that objects detected by the radardevice 21 will be referred to as radar-detected objects.

The radar device 21 also outputs, to the ECU 10, the obtained firstdetection information about the radar-detected object in the firstperiod.

The imaging device 22 is designed as a camera device, such as a CCDcamera device, a CMOS image sensor device, or a near-infrared cameradevice. For example, the imaging device 22 is mounted to the center of apredetermined portion, such as the upper end of the front windshield, ofthe own vehicle 50 in the vehicle width direction at a predeterminedheight. The imaging device 22 has an optical axis extending in front ofthe own vehicle 50. The imaging device 22 has a region, i.e. an imagingrange, that horizontally extends around the optical axis within apredetermined angular range, i.e. a predetermined angle of view. Theimaging device 22 captures, from the predetermined height, i.e. from ahigher point of view, images of the region, i.e. the imaging range inthe second period, and sends, to the ECU 10, the captured images in thesecond period as second detection information. Note that a monocularcamera device or a stereo camera device can be used as the imagingdevice 22, and a monocular camera device is used as the imaging device22 in the present embodiment.

Each of the captured images has a predetermined height in its verticaldirection and a width in its horizontal direction.

Target objects detected based on the images captured by the imagingdevice 22 will be referred to as image-detected objects.

The navigation device 23 is configured to provide road information abouta road on which the own vehicle 50 is travelling to the ECU 10.

The navigation device 23 includes a memory 23 a, a controller 23 b, anda display unit 23 c. The memory 23 a stores map information M includingroads on which the own vehicle 50 can travel, and including peripheriesaround each road.

The controller 23 b receives GPS signals from GPS satellites, anddetermines the current location of a predetermined point, such as thecenter of gravity, of the own vehicle 50 based on the received GPSsignals. The current location of the own vehicle 50 can be expressed asa corresponding longitude and a corresponding latitude. Then, thecontroller 23 b selects, from the memory 23 a, a map on and around thecurrent location of the own vehicle 50, and causes the display unit 23 cto display the map on which the current location of the own vehicle 50is displayed. In response to driver's input of a desired destinationfrom the current location of the own vehicle 50, the controller 23 bcauses the display unit 23 c to display one or more suitable routes tothe destination from the current location of the own vehicle 50. Thisnavigates the driver to drive the own vehicle 50 in accordance with aselected one of the suitable routes to the destination.

The navigation device 23 is also capable of cyclically accessingexternal infrastructural systems FS that can deliver traffic and travelinformation to road vehicle drivers. Each cyclic access obtains variouspieces of traffic information about the roads located on and around thecurrent location of the own vehicle 50. The various pieces of trafficinformation include

(1) Information indicative of the number of lanes in each of roadslocated within a predetermined distance area around the current locationof the own vehicle 50

(2) Information indicative of the locations of intersections within thepredetermined distance area around the current location of the ownvehicle 50

(3) Information indicative of the gradients of respective sections ofeach road located on and around the current location of the own vehicle50

The navigation device 23 is further capable of sending the obtainedtraffic information to the ECU 10 for each cyclic access.

The cruise assist devices 30 include, for example, a warning device 30a, a brake device 30 b, and a steering device 30 c. The warning device30 a includes a speaker and/or a display mounted in the compartment ofthe own vehicle 50. The warning device 30 a is configured to outputwarnings including, for example, warning sounds and/or warning messagesto inform the driver of the presence of an object in response to acontrol instruction sent from the ECU 10.

The brake device 30 b is configured to brake the own vehicle 50. Thebrake device 30 b is activated in response to a control instruction sentfrom the ECU 10 when the ECU 10 determines that there is a highprobability of collision of the own vehicle 50 with an object.Specifically, the brake device 30 b performs a brake-assist function ofincreasing braking force, which is based on the driver's brakeoperation, to the own vehicle 50, or an automatic brake function ofautomatically braking the own vehicle 50 if there is no brakingoperation by the driver.

The steering device 30 c is configured to control the travelling courseof the own vehicle 50. The steering device 30 c is activated in responseto a control instruction sent from the ECU 10 when the ECU 10 determinesthat there is a high probability of collision of the own vehicle 50 withan object. Specifically, the steering device 30 c performs a steeringassist function of assisting a driver's steering operation of thesteering wheel of the own vehicle 50, or an automatic steering functionof automatically steering the own vehicle 50 if there is no steeringoperation by the driver.

The ECU 10 is designed as, for example, a microcomputer including a CPU11, a memory 12 comprised of at least a ROM 12 a, a RAM 12 b, and/or asemiconductor memory such as a flash memory. The ECU 10 includes an I/Odevice (I/O) 13 connected via input ports to the radar device 21, theimaging device 22, and the cruise assist devices 30.

The various functions of the PCS system 100 are implemented by the CPU11 in executing programs that are stored in non-transitory recordingmedia. For example, the memory 12 serves as the non-transitory recordingmedia in which the programs are stored. Furthermore, the CPU 11 executesthe programs, thus executing methods corresponding to the programs. ThePCS system 100 is not necessarily configured with a singlemicrocomputer, and it would be equally possible to have a plurality ofmicrocomputers.

In particular, the ECU 10 is configured to

1. Recognize at least one object in accordance with the first detectioninformation input from the radar device 21 and the second detectioninformation including a captured image input from the imaging device 22

2. Perform a PCS control task based on the cruise assist devices 30 forthe recognized at least one object

The following describes the details of the PCS control task carried outby the ECU 10.

The ECU 10 according to the present embodiment defines a relativecoordinate system, i.e. an XY coordinate system, XY in, for example, astorage space of the memory 12; the relative coordinate system XY has

(1) The center of the front of the own vehicle 50 as its origin or itsreference point O

(2) The width direction of the own vehicle 50 passing through the originas its X axis

(3) The travelling direction of the own vehicle 50 passing through theorigin as its Y axis, in other words, a reference axis

The ECU 10 obtains, based on the relative position, azimuth, andrelative speed of a radar-detected object relative to the own vehicle50, a radar-detected position of the radar-detected object identified bya distance and a horizontal azimuth of the radar-detected objectrelative to the own vehicle 50 on the relative coordinate system XY setforth above.

In addition, the ECU 10 obtains, based on a captured image as the seconddetection information, an image-detected position of an image-detectedobject on the relative coordinate system XY. Then, the ECU 10 determineswhether the radar-detected object is identical with the image-detectedobject based on the radar-detected position of the radar-detected objectand the image-detected position of the image-detected object.

The following describes the radar-detected position of a radar-detectedobject and the image-detected position of an image-detected object withreference to FIG. 2 in which the relative coordinate system, i.e. X-Ycoordinate system, XY is illustrated.

First, the ECU 10 obtains, as the radar-detected position of aradar-detected object, a radar detection point Pr on the relativecoordinate system XY in accordance with a relative distance r1 and ahorizontal azimuth, i.e. a horizontal azimuth angle, θr of theradar-detected object relative to the own vehicle 50. The radardetection point Pr serves as first location information about theradar-detected object.

As illustrated in FIG. 2, the relative distance r1 represents a minimumdistance between the reference point O of the own vehicle 50 and, forexample, the center of the rear end of the radar-detected object, andthe horizontal azimuth θr represents a horizontal angle of a line L1connecting between the reference point O and the center of the rear endof the radar-detected object relative to the reference axis (Y axis).This enables the radar detection point Pr to be expressed as Pr(r1, θr).

Additionally, the ECU 10 obtains, as the image-detected position of animage-detected object, an image detection point Pi on the relativecoordinate system XY in accordance with a relative distance r2 and ahorizontal azimuth, i.e. a horizontal azimuth angle, θi of theimage-detected object relative to the own vehicle 50. The imagedetection point Pi serves as second location information about theimage-detected object.

As illustrated in FIG. 2, the relative distance r2 represents a minimumdistance between the reference point O of the own vehicle 50 and, forexample, the center of the lower end of the image-detected object, andthe horizontal azimuth θi represents a horizontal angle of a line L2connecting between the reference point O and the center of the lower endof the image-detected object relative to the reference axis (Y axis).This enables the image detection point Pi to be expressed as Pi(r2, θi).

That is, the ECU 10 calculates the relative distance r2 of theimage-detected object relative to the reference point O of the ownvehicle 50 based on the position of the center of the lower end of theimage-detected target in the captured image in the vertical direction.

Next, the ECU 10 sets, in the relative coordinate system XY, a radarsearch region Rr in accordance with the radar detection point Pr.

Specifically, the radar search region Rr has a longitudinal width andopposing lateral widths. The longitudinal width is an assumed erroramount set with reference to the radar detection point Pr of theradar-detected object in a distance direction. Each of the opposinglateral widths is also an assumed error amount set with reference to theradar detection point Pr of the radar-detected object in an azimuthdirection. The distance direction is defined as the direction of thedistance between the reference point O and the radar detection point Pr,and the azimuth direction is defined as the direction along the angularchange of the azimuth angle θr relative to the reference axis (Y axis).The assumed error amount of each of the distance direction and theazimuth direction of the radar search region Rr has been set beforehandbased on the characteristics of the radar device 21.

The longitudinal width of the radar search region Rr in the distancedirection will be referred to as a longitudinal width W1, and thelateral widths of the radar search region Rr in the azimuth directionwill be respectively referred to as lateral widths W2 a and W2 b.

For example, the radar search region Rr includes the radar detectionpoint Pr(r1, θr), and has a substantially rectangular shape with thelongitudinal width W1 as its longitudinal side and the lateral widths W2a and W2 b as its opposing lateral sides. The lateral side W2 b, whichis the farther from the origin O than the lateral side W2 a, is set tobe larger than the lateral side W2 a.

Similarly, the ECU 10 sets, in the relative coordinate system XY, animage search region Ri in accordance with the image detection point Pi.

Specifically, the image search region Ri has a longitudinal width andopposing lateral widths. The longitudinal width is an assumed erroramount set with reference to the image detection point Pi of theimage-detected object in a distance direction. Each of the opposinglateral widths is also an assumed error amount set with reference to theimage detection point Pi of the image-detected object in an azimuthdirection. The distance direction is defined as the direction of thedistance between the reference point O and the image detection point Pi,and the azimuth direction is defined as the direction along the angularchange of the azimuth angle θi relative to the reference axis (Y axis).The assumed error amount of each of the distance direction and theazimuth direction of the image search region Ri has been set beforehandbased on the characteristics of the imaging device 22.

The longitudinal width of the image search region Ri in the distancedirection will be referred to as a longitudinal width W11, and thelateral widths of the image search region Ri in the azimuth directionwill be respectively referred to as lateral widths W12 a and W12 b.

For example, the image search region Ri includes the image detectionpoint Pi(r2, θi), and has a substantially rectangular shape with thelongitudinal width W11 as its longitudinal side and the lateral widthsW12 a and W12 b as its opposing lateral sides. The lateral side W12 b,which is the farther from the origin O than the lateral side W12 a, isset to be larger than the lateral side W12 a.

That is, the ECU 10 determines whether the radar-detected object isidentical with the image-detected object in accordance with apredetermined determination condition based on the radar detection pointPr and the image detection point Pi.

In particular, the ECU 10 uses, as the identification determinationcondition, determination of whether the radar search region Rr definedbased on the radar detection point Pr is at least partially overlappedwith the image search region Ri defined based on the image detectionpoint Pi to thereby determine whether the radar-detected object isidentical with the image-detected object.

For example, in FIG. 2, because the radar search region Rr and the imagesearch region Ri have a partly overlapped portion therebetween, the ECU10 determines that the radar-detected object is identical with theimage-detected object. Upon determining that the radar-detected objectis identical with the image-detected object, the ECU 10 fuses, i.e.combines, the radar detection point Pr and the image detection point Piwith each other to thereby generate a new fusion position for a sametarget object.

For example, in FIG. 2, the ECU 10 selects the relative distance r1,which is higher in accuracy than the azimuth angle θr, from the radardetection point Pr(r1, θr), and selects the azimuth angle θi, which ishigher in accuracy than the relative distance r2, from the imagedetection point Pi(r2, θi). Then, the ECU 10 fuses, i.e. combines, theselected relative distance r1 and the selected azimuth angle θi witheach other, thus generating a new fusion detection point Pf(r1, θi) forthe same target object; the same target object will be referred to as afusion target object.

Next, the ECU 10 determines whether there is a possibility of the ownvehicle 50 colliding with the fusion target object.

For example, the ECU 10 has a predetermined collision prediction regionCPR previously defined for the own vehicle 50 in the relative coordinatesystem XY.

For example, the collision prediction region CPR

1. Has the center axis corresponding to the Y axis illustrated in FIG.30

2. Has a rightward width based on a rightward limit XR in the rightwarddirection relative to the travelling direction corresponding to theX-axis direction

3. Has a leftward width based on a leftward limit XL in the rightwarddirection relative to the travelling direction

4. Has a predetermined length, i.e. depth, L from the reference point Oof the own vehicle 50 along the Y axis direction

That is, the ECU 10 calculates a lateral coordinate of the fusiondetection point Pf(r1, θi) relative to the Y axis. Then, the ECU 10determines whether the lateral coordinate of the fusion detection pointPf(r1, θi) is located within the collision prediction region CPR tothereby determine whether there is a possibility of collision of the ownvehicle 50 with the target object.

Upon determining that the lateral coordinate of the fusion detectionpoint Pf(r1, θi) is located outside the collision prediction region CPR,the ECU 10 determines that there is no possibility of collision of theown vehicle 50 with the fusion target object.

Otherwise, upon determining that the lateral coordinate of the fusiondetection point Pf(r1, θi) is located within the collision predictionregion CPR, the ECU 10 determines that there is a possibility ofcollision of the own vehicle 50 with the fusion target object.

Upon determining that there is a possibility of collision of the ownvehicle 50 with the target object, the ECU 10 calculates a time tocollision (TTC), which represents a margin time until which the ownvehicle 50 would collide with the fusion target object, in accordancewith the relative position of the fusion target object and the relativespeed between the own vehicle 50 and the fusion target object.

Then, the ECU 10 compares the calculated TIC with predeterminedactivation times of the respective cruise-assist devices 30, i.e.thresholds representing the respective activation times to therebyselectively activate at least one of the cruise-assist devices 30.

Specifically, the thresholds are respectively set for the warning device30 a, the brake device 30 b, and the steering device 30 c. The relativesizes among the thresholds are identical to the above relative sizesamong the activation times.

The thresholds respectively set for the warning device 30 a, the brakedevice 30 b, and the steering device 30 c are for example determinedsuch that the threshold for the warning device 30 a is larger than thethreshold for the brake device 30 b, and the threshold for the steeringdevice 30 c is larger than the threshold for the brake device 30 b.

If the own vehicle 50 approaches the fusion target object, so that theTTC becomes lower than the threshold for the activation timing for thewarning device 30 a, the ECU 10 determines that it is time to activatethe warning device 30 a, thus transmitting an activation control signalto the warning device 30 a. This causes the warning device 30 a to beactivated to output warnings, thus informing the driver of a risk ofcollision with the fusion target object.

After activation of the warning device 30 a, if the own vehicle 50further approaches the fusion target object with the brake pedal beingnot depressed by the driver, so that the ITC further decreases to becomelower than the threshold for the activation timing for the automaticbrake function of the brake device 30 b, the ECU 10 determines that itis time to activate the automatic brake function of the brake device 30b, thus transmitting an activation control signal to the automatic brakefunction of the brake device 30 b. This causes the brake device 30 b tobe activated to perform braking control of the own vehicle 50.

On the other hand, after activation of the warning device 30 a, if theown vehicle 50 further approaches the fusion-based object despite thedriver's depression of the brake pedal, so that the TC further decreasesto become lower than the threshold for the activation timing for thebrake-assist function of the brake device 30 b, the ECU 10 determinesthat it is time to activate the brake-assist function of the brakedevice 30 b, thus transmitting an activation control signal to thebrake-assist function of the brake device 30 b. This causes the brakedevice 30 b to be activated to increase braking force based on thedriver's depression of the braking pedal.

After activation of the brake device 30 b, if the own vehicle 50 furtherapproaches the fusion target object, so that the TTC further decreasesto become lower than the threshold for the activation timing for thesteering device 30 c, the ECU 10 determines that it is time to activatethe steering device 30 c, thus transmitting an activation control signalto the steering device 30 c. This causes the steering device 30 c to beactivated to perform forcible steering control of the own vehicle 50.

The above PCS control task aims to avoid a collision between the ownvehicle 50 and the fusion target object or mitigate damage due tocollision therebetween.

As described above, the ECU 10 calculates the relative distance r2 ofthe image-detected object relative to the reference point O of the ownvehicle 50 based on the position of the center of the lower end of theimage-detected target in the captured image in the vertical direction.

FIG. 4 schematically illustrates a situation where the own vehicle 50 istravelling on a reference road section whose gradient or inclinationangle relative to a predetermined flat road section is zero degrees,i.e. the reference road section is the flat road section. FIG. 4 alsoschematically illustrates that a preceding vehicle 60 as theimage-detected object is travelling or located on an objective roadsection whose upward gradient or inclination angle relative to thepredetermined flat road section is predetermined A degrees greater thanzero degrees, so that the preceding vehicle 60 is located to be higherthan the own vehicle 50.

We focus on the fact that the preceding vehicle 60 in an image capturedby the imaging device 22 of the own vehicle 50 in this situationillustrated in FIG. 4 is located to be higher than a preceding vehiclethat is travelling on the same reference road section.

Unfortunately, it is difficult for the ECU 10 to obtain, from an imagecaptured by the imaging device 22, the upward gradient of the objectiveroad section on which the preceding vehicle 60 is travelling relative tothe reference road section. This may result in the image detection pointPi of the preceding vehicle 60 being obtained, based on the capturedimage, as an erroneous image detection point Pi, so that the precedingvehicle 60 may be detected as an erroneous preceding vehicle 70.

For this reason, there may be a gap ΔD between the relative distance D2between the reference point O of the own vehicle 50 and the erroneousimage detection point Pi and an actual relative distance D1 between thereference point O of the own vehicle 50 and the center of the rear endof the actual preceding vehicle 60. That is, the relative distance D2between the reference point O of the own vehicle 50 and the erroneousimage detection point Pi may be longer than the actual relative distanceD1.

In contrast, let us consider an additional situation where

(1) The own vehicle 50 is travelling on the reference road section whosegradient or inclination angle relative to the predetermined flat roadsection is zero degrees

(2) A preceding vehicle 60 as the fusion target object is travelling onan objective road section whose downward gradient or inclination anglerelative to the predetermined reference road section is predetermineddegrees smaller than zero degrees, so that the preceding vehicle 60 islocated to be lower than the own vehicle 50

Note that an upward inclination angle is set to have a positivepolarity, and a downward inclination angle is set to have a negativepolarity.

Like the upward slope of the objective road section, there may be a gapΔD between the relative distance D2 between the reference point O of theown vehicle 50 and an erroneous image detection point Pi and an actualrelative distance D1 between the reference point O of the own vehicle 50and the center of the rear end of the actual preceding vehicle 60. Thatis, the relative distance D2 between the reference point O of the ownvehicle 50 and the erroneous image detection point Pi may be shorterthan the actual relative distance D1.

The gap ΔD may cause the location of the image search region Riestablished based on the erroneous image detection point Pi to bedeviated from an actual location of the image search region Ri in thedistance direction. This may make it difficult for the ECU 10 toaccurately determine whether the radar-detected object is identical withthe image-detected object.

From this viewpoint, the ECU 10 according to the present embodiment isconfigured to

(1) Calculate a relative gradient difference Δα between the referenceroad section on which the own vehicle 50 is travelling and the objectiveroad section on which the image-detected object is located

(2) Correct, based on the calculated relative gradient difference Δα,the location of the image search region Ri in the distance direction tothereby calculate a corrected image search region

(3) Determine whether the radar-detected object is identical with theimage-detected object in accordance with the radar search region Rr andthe corrected image search region

This configuration enables determination of whether the radar-detectedobject is identical with the image-detected object to be accuratelycarried out even if there is a relative gradient difference Δα betweenthe reference road section on which the own vehicle 50 is travelling andthe objective road section on which the image-detected object islocated.

For example, the ECU 10 carries out the following gradient differencecalculation task to thereby calculate the gradient difference Δα.

Specifically, the ECU 10 obtains gradient information about thereference road section on which the own vehicle 50 is travelling. Forexample, the ECU 10 obtains, from the navigation system 23, the currentlocation of the own vehicle 50 and information about the reference roadsection determined by the current location of the own vehicle 50. Then,the ECU 10 obtains, from the information about the road at the currentlocation of the own vehicle 50 stored in the map information M, aninclination angle α1 of the reference road section on which the ownvehicle 50 is travelling. Note that, if the own vehicle 50 incorporatestherein a gyro sensor or an inclination angle sensor for measuring aninclination angle of the own vehicle 50 relative to a reference flatplane, the ECU 10 can obtain the inclination angle α1 of the referenceroad section on which the own vehicle 50 is travelling in accordancewith a value measured by the gyro sensor or inclination angle sensor.

In addition, the ECU 10 obtains gradient information about the objectiveroad section on which the image-detected object, such as a precedingvehicle 60, is travelling. For the sake of simplified description, thefollowing describes the gradient difference calculation task using thepreceding vehicle 60 as the fusion target object.

For example, the ECU 10 obtains, from the navigation system 23,information about the objective road section determined based on anestimated current location of the preceding vehicle 60. Then, the ECU 10obtains, from the information about the road at the estimated currentlocation of the preceding vehicle 60 stored in the map information M, aninclination angle α2 of the objective road section on which thepreceding vehicle 60 is travelling.

Specifically, the ECU 10 can estimate the current location of thepreceding vehicle 60 based on the current location of the own vehicle 50and the relative distance of the image detection point Pi relative tothe reference point O of the own vehicle 50.

In particular, as illustrated in FIG. 4, if there is an upward slopesection or a downward slope section of the road in front of the ownvehicle 50, the relative distance of the image detection point Pirelative to the reference point O of the own vehicle 50 may contain anerror.

In order to address such an issue, the ECU 10 is configured to obtain,as the gradient information about the objective road section on whichthe preceding vehicle 60 is travelling, gradient information about apredetermined first inclination detection range E1 including the imagedetection point Pi (see FIG. 5). The first inclination detection rangeE1 is defined as a linear range along the distance direction of theimage detection point Pi from a first margin to a second margininclusive; the first margin is obtained by subtraction of apredetermined value ΔE1 from the relative length r2 at the imagedetection point Pi, which is referred to as (r2−ΔE1), and the secondmargin is obtained by the sum of the relative length r2 at the imagedetection point Pi and the predetermined value ΔE1, which is referred toas (r2+ΔE1).

For example, the ECU 10 calculates an inclination angle at each ofplural sampling points in the first inclination detection range E1, andcalculates the average value of the calculated inclination angles as aninclination angle α2 of the objective road section on which thepreceding vehicle 60 is travelling. The ECU 10 can change the length ofthe first inclination detection range E1 along the distance directiondepending on the relative distance r2 of the image detection point Pi.

In addition, the ECU 10 can be configured to obtain, as the gradientinformation about the objective road section on which the precedingvehicle 60 is travelling, gradient information about a predeterminedsecond inclination detection range E2 including the image detectionpoint Pi (see FIG. 5). The second inclination detection range E2 isdefined as an azimuth range along the azimuth direction of the imagedetection point Pi from a first margin to a second margin inclusive; thefirst margin is obtained by subtraction of a predetermined angle Δθ fromthe azimuth angle θi at the image detection point Pi, which is referredto as (θi−Δθ), and the second margin is obtained by the sum of theazimuth angle θi at the image detection point Pi and the predeterminedangle Δθ, which is referred to as (θi+Δθ).

For example, the ECU 10 calculates an inclination angle at each ofplural sampling points in the second inclination detection range E2, andcalculates the average value of the calculated inclination angles as theinclination angle α2 of the objective road section on which thepreceding vehicle 60 is travelling. The ECU 10 can change the length ofthe second inclination detection range E2 along the azimuth directiondepending on the relative distance r2 of the image detection point Pi.

As a further example, the ECU 10 can calculate an inclination angle ateach of plural sampling points in the rectangular region defined by thefirst and second inclination detection ranges E1 and E2, and calculatesthe average value of the calculated inclination angles as theinclination angle α2 of the objective road section on which thepreceding vehicle 60 is travelling.

The inclination angle α1 represents a positive value upon the referenceroad section on which the own vehicle 50 is travelling being an upslope,and a negative value upon the reference road section being a downslope.Similarly, the inclination angle α2 represents a positive value upon theobjective road section on which the preceding vehicle 60 is travellingbeing an upslope, and a negative value upon the objective road sectionbeing a downslope. In addition, the greater the gradient of the upslopeor downslope reference road section is, the greater the absolute valueof the inclination angle α1 is. Similarly, the greater the gradient ofthe upslope or downslope reference road section is, the greater theabsolute value of the inclination angle α2 is.

When obtaining the inclination angle α1 of the reference road section onwhich the own vehicle 50 is travelling and the inclination angle α2 ofthe objective road section on which the preceding vehicle 60 istravelling, the ECU 10 calculates the relative gradient difference Δαbetween the reference road section on which the own vehicle 50 istravelling and the objective road section on which the preceding vehicle60 is travelling. For example, the ECU 10 subtracts the inclinationangle α1 from the inclination angle α2 to thereby calculate the relativegradient difference Δα. The relative gradient difference Δα represents apositive value upon the objective road section on which the precedingvehicle 60 is travelling being an upslope (see FIG. 4), and a negativevalue upon the objective road section on which the preceding vehicle 60is travelling being a downslope.

After completion of calculation of the relative gradient difference Δα,the ECU 10 corrects, based on the calculated relative gradientdifference Δα, the location of the image search region Ri in thedistance direction to thereby calculate a corrected image search region.

The following describes how the ECU 10 corrects the image search regionRi with reference to FIGS. 5 to 7.

First, the following describes how the ECU 10 corrects the image searchregion Ri if the objective road section on which the preceding vehicle60 is travelling is an upslope relative to the reference road section onwhich the own vehicle 50 is travelling, so that the relative gradientdifference Δα between the reference and objective road sections has apositive value with reference to FIGS. 5 and 6 (see FIG. 5). That is,FIG. 5 illustrates the radar search region Rr and the image searchregion Ri obtained by the ECU 10 under the situation illustrated in FIG.4.

Under the situation illustrated in FIG. 5, the ECU 10 corrects the imagesearch region Ri based on the relative gradient difference Δα.

First, the ECU 10 corrects the image detection point Pi to be closer tothe own vehicle 50 to thereby obtain a corrected image detection pointCPi.

Specifically, the ECU 10 sets a correction amount DA for the imagedetection point Pi, and moves the image detection point Pi to be closerto the own vehicle 50 by the correction amount DA in the distancedirection.

The ECU 10 for example sets the correction amount DA for the imagedetection point Pi in accordance with the relative gradient differenceΔα and the position of the center of the lower end of the precedingvehicle 60 in the captured image in the vertical direction.

FIG. 6A schematically illustrates a captured image CI in which thepreceding vehicle 60 is included. The position of the center of thelower end of the preceding vehicle 60 is illustrated as PP.

We consider that, the greater the relative gradient difference Δα is,the greater the deviation of the image detection point Pi from thelocation of an actual image detection point is. In addition, we considerthat, the higher the position PP of the center of the lower end of thepreceding vehicle 60 in the captured image CI in the vertical directionis, the greater the deviation of the image detection point Pi from thelocation of the actual image detection point is.

In accordance with the above considerations, the ECU 10 includesrelationship information I1 stored in, for example, the ROM 12 b of thememory 12. The relationship information I1 includes

(1) The first relationship between values of the relative gradientdifference Δα and values of the correction amount DA

(2) The second relationship between values of the position PP of thecenter of the lower end of the preceding vehicle 60 in the capturedimage CI in the vertical direction and values of the correction amountDA

For example, FIG. 6A illustrates that the bottom end of the capturedimage CI in the vertical direction represents the value of zero in thevertical direction, and the top end of the captured image CI representsa maximum value MAX in the vertical direction. A value of the positionPP of the center of the lower end of the preceding vehicle 60 in thevertical direction of the captured image CI is determined based on themaximum value MAX and the ratio of the length of the point PP from thebottom end of the captured image CI to the length of the upper end ofthe captured image CI.

FIG. 6B schematically illustrates the first and second relationships asa graph. The graph has a horizontal axis and a vertical axis. Thehorizontal axis represents the values of the position PP of the centerof the lower end of the preceding vehicle 60 in the captured image inthe vertical direction. The vertical axis represents the values of thecorrection amount DA.

Specifically, the graph shows plural characteristics curves CCn eachrepresenting a relationship between the values of the correction amountDA and the values of the position PP of the center of the lower end ofthe preceding vehicle 60 in the captured image CI in the verticaldirection while the relative gradient difference Δα is set to acorresponding value. That is, the characteristics curves CCn areprepared for the respective values of the relative gradient differenceΔα.

Specifically, the ECU 10 obtains, from a captured image CI, the value ofthe position PP of the center of the lower end of the preceding vehicle60, and calculates a value of the relative gradient difference Δα setforth above. Then, the ECU 10 extracts, from the relationshipinformation I1, a value of the correction amount DA matching with theobtained value of the position PP of the center of the lower end of thepreceding vehicle 60 and the calculated value of the relative gradientdifference Δα.

For example, FIG. 6B illustrates that, the greater the relative gradientdifference Δα is, the greater the value of the correction amount DA is,and the higher the position PP of the center of the lower end of thepreceding vehicle 60 is, the greater the value of the correction amountDA is.

Following the obtaining of the corrected image detection point CPi setforth above, the ECU 10 sets, based on the corrected image detectionpoint CPi, a corrected image searching region CRi in the relativecoordinate system XY next.

Specifically, the ECU 10 sets, in the relative coordinate system XY, thecorrected searching region CRi around the corrected image detectionpoint CPi such that the corrected searching region Cri has alongitudinal width Ca and opposing lateral widths CRia and CRib.

Let us assume that a normal searching region set around the correctedimage detection point CPi is defined as a region URi having alongitudinal width Ua and opposing lateral widths URia and URib. Thelongitudinal width Ua is an assumed error amount set with reference tothe corrected image detection point CPi in the distance direction, andeach of the opposing lateral widths URia and URib is also an assumederror amount set with reference to the corrected image detection pointCPi in the azimuth direction.

As compared with the normal search region URi, the longitudinal width Caof the corrected image detection point CPi in the distance direction isset to be smaller than the longitudinal width Ua of the normal searchregion URi. For example, the ECU 10 obtains the longitudinal width Ua,and multiplies the longitudinal width Ua by a predetermined percentage,such as 60%, thus obtaining the longitudinal width Ca of the correctedimage detection point CPi. In contrast, as compared with the normalsearch region URi, each of the opposing lateral widths CRia and CRib ofthe corrected image detection point CPi in the azimuth direction is setto be identical to the corresponding one of the opposing lateral widthsURia and URib of the normal search region URi.

That is, the ECU 10 corrects the location of the image search region Rito be closer to the own vehicle 50, and corrects the longitudinal widthof the moved image search region Ri to be narrower than the normal widthUa of the normal search region URi around the corrected image detectionpoint CPi having a corrected relative distance r2 a and the azimuthangle θi, which will be referred to as CPi(r2 a, θi). In contrast, theECU 10 maintains the radar search region Rr unchanged.

Next, the following describes how the ECU 10 corrects the image searchregion Ri if the objective road section on which the preceding vehicle60 is travelling is a downslope relative to the reference road sectionon which the own vehicle 50 is travelling, so that the relative gradientdifference Δα between the reference and objective road sections has anegative value with reference to FIG. 7. That is, FIG. 7 illustrates theradar search region Rr and the image search region Ri obtained by theECU 10 under the situation where the relative gradient difference Δαbetween the reference and objective road sections has a negative value.

Reference characters of elements illustrated in FIG. 7, which aresubstantially identical to the corresponding elements illustrated inFIG. 5, are set to be identical to the corresponding referencecharacters illustrated in FIG. 5. Descriptions of the elementsillustrated in FIG. 7, which are substantially identical to thecorresponding elements illustrated in FIG. 5, are therefore omitted orsimplified.

The ECU 10 for example sets the correction amount DA for the imagedetection point Pi in accordance with the relative gradient differenceΔα and the position of the center of the lower end of the precedingvehicle 60 in the captured image CI in the vertical direction.

That is, the ECU 10 includes relationship information I2 stored in, forexample, the ROM 12 b of the memory 12. The relationship information I2includes

(1) The first relationship between values of the relative gradientdifference Δα and values of the correction amount DA

(2) The second relationship between values of the position PP of thecenter of the lower end of the preceding vehicle 60 in the capturedimage CI in the vertical direction and values of the correction amountDA

FIG. 8 schematically illustrates the first and second relationships as agraph. The graph has a horizontal axis and a vertical axis. Thehorizontal axis represents the values of the position PP of the centerof the lower end of the preceding vehicle 60 in the captured image inthe vertical direction. The vertical axis represents the values of thecorrection amount DA.

Specifically, the graph shows plural characteristics curves CCm eachrepresenting a relationship between the values of the correction amountDA and the values of the position PP of the center of the lower end ofthe preceding vehicle 60 in the captured image CI in the verticaldirection while the relative gradient difference Δα is set to acorresponding value. That is, the characteristics curves CCm areprepared for the respective values of the relative gradient differenceΔα.

Specifically, the ECU 10 obtains, from a captured image CI, the value ofthe position PP of the center of the lower end of the preceding vehicle60, and calculates a value of the relative gradient difference Δα setforth above. Then, the ECU 10 extracts, from the relationshipinformation I2, a value of the correction amount DA matching with theobtained value of the position PP of the center of the lower end of thepreceding vehicle 60 and the calculated value of the relative gradientdifference Δα.

For example, FIG. 7 illustrates that, the greater an absolute value ofthe relative gradient difference Δα is, the greater the value of thecorrection amount DA is, and the lower the position PP of the center ofthe lower end of the preceding vehicle 60 is, the greater the value ofthe correction amount DA is.

Following the obtaining of the corrected image detection point CPi setforth above, the ECU 10 sets, based on the corrected image detectionpoint CPi, a corrected image searching region CRi in the relativecoordinate system XY next.

Specifically, the ECU 10 sets, in the relative coordinate system XY, thecorrected searching region CRi around the corrected image detectionpoint CPi such that the corrected searching region CRi has alongitudinal width Ca1 and opposing lateral widths CRia and CRib.

Let us assume that a normal searching region set around the correctedimage detection point CPi is defined as a region URi having alongitudinal width Ua and opposing lateral widths URia and URib. Thelongitudinal width Ua is an assumed error amount set with reference tothe corrected image detection point CPi in the distance direction, andeach of the opposing lateral widths URia1 and URib1 is also an assumederror amount set with reference to the corrected image detection pointCPi in the azimuth direction.

As compared with the normal search region URi, the longitudinal width Caof the corrected image detection point CPi in the distance direction isset to be smaller than the longitudinal width Ua1 of the normal searchregion URi1. In contrast, as compared with the normal search regionURi1, each of the opposing lateral widths CRia and CRib of the correctedimage detection point CPi in the azimuth direction is set to beidentical to the corresponding one of the opposing lateral widths URiaand URib of the normal search region URi.

That is, the ECU 10 corrects the location of the image search region Rito be closer to the own vehicle 50, and corrects the longitudinal widthof the moved image search region Ri to be narrower than the normal widthUa of the normal search region URi around the corrected image detectionpoint CPi.

Next, the ECU 10 determines whether the radar search region Rr and thecorrected image search region CRi are at least partly overlapped witheach other.

Upon determining that the radar search region Rr and the corrected imagesearch region CRi are at least partly overlapped with each other, theECU 10 determines that the radar-detected object corresponding to theradar search region Rr is identical to the image-detected objectcorresponding to the image search region Ri.

Otherwise upon determining that the radar search region Rr and thecorrected image search region CRi are not overlapped with each other,the ECU 10 determines that the radar-detected object corresponding tothe radar search region Rr is a different object from the image-detectedobject corresponding to the image search region Ri.

Next, the following describes a fusion determination routine carried outby the ECU 10 with reference to FIG. 9. The ECU 10 is programmed tocarry out the fusion object determination routine every predeterminedperiod. Hereinafter, one fusion determination routine periodicallyperformed by the ECU 10 will be referred to as a cycle.

When starting the fusion determination routine, the ECU 10 obtains theradar detection point Pr as the radar-detected position of aradar-detected object measured by the radar device 21 in step S11, andsets, in the relative coordinate system XY, the radar search region Rrin accordance with the radar detection point Pr in step S12.

That is, the ECU 10 serves as, for example, a first setter 10 a to setthe radar search region Rr in the relative coordinate system XY in stepsS11 and S12.

Next, the ECU 10 obtains the image detection point Pi as theimage-detected position of an image-detected object measured by theimaging device 22 in step S13, and sets, in the relative coordinatesystem XY, the image search region Ri in accordance with the imagedetection point Pi in step S14.

That is, the ECU 10 serves as, for example, a second setter 10 b to setthe image search region Ri in the relative coordinate system XY in stepsS13 and S14.

Following the operation in step S14, the ECU 10 obtains the gradientinformation about the reference road section on which the own vehicle 50in step S15. For example, the ECU 10 obtains, from the navigation system23, the current location of the own vehicle 50 and information about thereference road section determined by the current location of the ownvehicle 50 in step S15. Then, the ECU 10 obtains, from the informationabout the road at the current location of the own vehicle 50, theinclination angle α1 of the reference road section on which the ownvehicle 50 is travelling in step S15.

Next, the ECU 10 obtains the gradient information about the objectiveroad section on which the image-detected object, such as the precedingvehicle 60, is travelling or located in step S16. For example, the ECU10 obtains, from the navigation system 23, information about theobjective road section determined based on the estimated currentlocation of the preceding vehicle 60 in step S16. Then, the ECU 10obtains, from the information about the road at the estimated currentlocation of the preceding vehicle 60, the inclination angle α2 of theobjective road section on which the preceding vehicle 60 is travellingin step S16.

Then, the ECU 10 calculates the relative gradient difference Δα betweenthe reference road section on which the own vehicle 50 is travelling andthe objective road section on which the preceding vehicle 60 istravelling or located in step S17. For example, the ECU 10 subtracts theinclination angle α1 from the inclination angle α2 to thereby calculatethe relative gradient difference Δα in step S17. The relative gradientdifference Δα represents a positive value upon the objective roadsection on which the preceding vehicle 60 is travelling being anupslope, and a negative value upon the objective road section on whichthe preceding vehicle 60 is travelling being a downslope.

That is, the ECU 10 serves as, for example, an inclination calculator ora gradient calculator 10 c to calculate the relative gradient differenceΔα in steps S15 to S17.

Following the operation in step S17, the ECU 10 determines whether thecalculated gradient difference Δα is equal to or more than a firstthreshold Th1 and equal to or less than a second threshold Th2 in stepS18. For example, the first threshold Th1 is set to be zero or anegative value close to zero, and the second threshold Th2 is set to bezero or a positive value close to zero.

Upon determining that the calculated gradient difference Δα is equal toor more than the first threshold Th1 and equal to or less than thesecond threshold Th2 (YES in step S18), the fusion determination routineproceeds to step S20. That is, if the calculated gradient difference Δαis zero or a value very close to zero, which is within the range fromthe first threshold Th1 to the second threshold Th2 inclusive, the ECU10 determines that there is no inclination difference between thereference road section on which the own vehicle 50 is travelling and theobjective road section on which the preceding vehicle 60 is travelling.This therefore enables the ECU 10 to determine that there is nodeviation of the location of the image search region Ri from the actuallocation of the image search region Ri in the distance direction.

Otherwise, upon determining that the calculated gradient difference Δαis less than the first threshold Th1 or more than the second thresholdTh2 (NO in step S18), the fusion determination routine proceeds to stepS19.

In step S19, the ECU 10 serves as, for example, a corrector 10 d tocorrect the image detection point Pi and the image search region Ribased on the gradient difference Δα.

Specifically, the ECU 10 determines whether the gradient difference Δαis less than the first threshold Th1 or more than the second thresholdTh2 in step S19 a of FIG. 10A.

Upon determining that the gradient difference Δα is more than the secondthreshold Th2 in step S19 a, the ECU 10 sets, in step S19 b, a value ofthe correction amount DA in accordance with

(1) A value of the gradient difference Δα

(2) A value of the position PP of the center of the lower end of thepreceding vehicle 60 in the captured image CI

(3) The relationship information I1

Then, the ECU 10 corrects the image detection point Pi to be closer tothe own vehicle 50 by the value of the correction amount DA to therebyobtain the corrected image detection point CPi in step S19 c.

Following the operation in step S19 c, the ECU 10 sets the correctedsearch region CRi around the corrected image detection point CPi suchthat the longitudinal width of the corrected image search region CRi isnarrower than the normal image search region URi around the correctedimage detection point CPi in step S19 d.

Otherwise, upon determining that the gradient difference Δα is less thanthe first threshold Th1 in step S19 a, the ECU 10 sets, in step S19 e, avalue of the correction amount DA in accordance with

(1) A value of the gradient difference Δα

(2) A value of the position PP of the center of the lower end of thepreceding vehicle 60 in the captured image CI

(3) The relationship information I2

Then, the ECU 10 corrects the image detection point Pi to be fartherfrom the own vehicle 50 by the value of the correction amount DA tothereby obtain the corrected image detection point CPi in step S19 f.

Following the operation in step S19 f, the ECU 10 sets the correctedsearch region CRi around the corrected image detection point CPi suchthat the longitudinal width of the corrected image search region CRi isnarrower than the normal image search region URi around the correctedimage detection point CPi in step S19 g.

After the affirmative determination in step S18 or after the operationin step S19, the ECU 10 serves as, for example, a determiner 10 e todetermine whether the radar-detected object corresponding to the radarsearch region Pr is identical with the image-detected objectcorresponding to the image search region Pi in accordance with thepredetermined identification determination condition based on the radarsearch region Rr and either the image search region Ri or the correctedimage search region CRi in step S20.

Specifically, in step S20, the ECU 10 uses, as the identificationdetermination condition, determination of whether the radar searchregion Rr is at least partially overlapped with the image search regionRi to thereby determine whether the radar-detected object is identicalwith the image-detected object upon the determination in step S18 beingaffirmative.

In contrast, upon the image search region Ri having been corrected tothe corrected image search region CRi, the ECU 10 uses, as theidentification determination condition, determination of whether theradar search region Rr is at least partially overlapped with thecorrected image search region CRi to thereby determine whether theradar-detected object is identical with the image-detected object instep S20.

Upon it being determined that the radar search region Rr is at leastpartially overlapped with the corrected image search region CRi, i.e.the identification determination condition is satisfied (YES in stepS20), the ECU 10 determines that the radar-detected object is identicalwith the image-detected object, the fusion determination routineproceeding to step S21. Otherwise, upon it being determined that theradar search region Rr is not overlapped with the corrected image searchregion CRi, i.e. the identification determination condition isunsatisfied (NO in step S20), the ECU 10 determines that theradar-detected object is not identical with the image-detected object,the fusion determination routine proceeding to step S22.

Note that, in step S20, the ECU 10 can determine whether theradar-detected object corresponding to the radar search region Pr isidentical with the image-detected object corresponding to the imagesearch region Pi in accordance with a second determination conditionbased on the radar detection point Pr and the image detection point Pi.

For example, in step S20 a of FIG. 10B, the ECU 10 calculates a radarTTC, which represents a margin time until which the own vehicle 50 wouldcollide with the radar detection point Pr, and calculates an image TTC,which represents a margin time until which the own vehicle 50 wouldcollide with either the image detection point Pi or the corrected imagedetection point CPi.

Then, in step S20 b, the ECU 10 calculates an absolute value of thedifference between the radar TC and the image TTC, and determineswhether the calculated absolute value of the difference between theradar TTC and the image TTC is less than a predetermined threshold B instep S20 c.

Upon determining that the calculated absolute value of the differencebetween the radar ITC and the image ITC is less than the predeterminedthreshold B, i.e. the second identification determination condition issatisfied (YES in step S20 c), the ECU 10 determines that theradar-detected object is identical with the image-detected object, thefusion determination routine proceeding to step S21. Otherwise, upon itbeing determined that the calculated absolute value of the differencebetween the radar TC and the image TTC is equal to or more than thepredetermined threshold B, i.e. the second identification determinationcondition is unsatisfied (NO in step S20 c), the ECU 10 determines thatthe radar-detected object is not identical with the image-detectedobject, the fusion determination routine proceeding to step S22.

In step S21, the ECU 10 fuses, i.e. combines, the radar detection pointPr(r1, θr) with the image detection point Pi(r2, θi) or the correctedimage detection point CPi(r2 a, θi), thus generating a new fusiondetection point Pf(r1, θi) for the same target object, i.e. the fusiontarget object.

Otherwise, in step S22, the ECU 10 maintains the radar detection pointPr(r1, θr) and the image detection point Pi(r2, θi) or the correctedimage detection point CPi(r2 a, θi) without generating the fusiondetection point Pf(r1, θi).

Thereafter, the ECU 10 executes a task for determining whether there isa possibility of the own vehicle 50 colliding with the fusion targetobject or each of the radar-detector object and the image-detectedobject.

As described above, the vehicle control apparatus, i.e. the ECU 10,according to the present embodiment obtains the following benefits.

Specifically, the vehicle control apparatus is configured to

(1) Calculate the gradient difference Δα between the reference roadsection on which the own vehicle 50 is travelling and the objective roadsection on which the preceding vehicle 60 is travelling

(2) Correct, based on the gradient difference Δα, the relative distanceof the image detection point Pi relative to the reference point O of theown vehicle 50 and the position of the image search region Ri in thedistance direction

(3) Determine whether the radar-detected object is identical with theimage-detected object based on the radar search region and the correctedimage search region CRi

This configuration enables the corrected image search region CRi onwhich the gradient difference Δα has been reflected to be obtained,making it possible to accurately determine whether the radar-detectedobject is identical with the image-detected object. That is, thisconfiguration enables the fusion detection point Pf to be accuratelyobtained even if the relative gradient difference Δα is generatedbetween the reference road section on which the own vehicle 50 istravelling and the objective road section on which the preceding vehicle60 is travelling.

Specifically, the vehicle control apparatus is configured to correct thelocation of the image search region Ri to be closer to the own vehicle50 if the objective road section on which the preceding vehicle 60 istravelling is an upslope relative to the reference road section on whichthe own vehicle 50 is travelling, i.e. if the gradient difference Δα isgreater than the second threshold Th2. In addition, the vehicle controlapparatus is configured to correct the location of the image searchregion Ri to be farther from the own vehicle 50 if the objective roadsection on which the preceding vehicle 60 is travelling is a downsloperelative to the reference road section on which the own vehicle 50 istravelling, i.e. if the gradient difference Δα is smaller than the firstthreshold Th1.

This configuration therefore enables the location of the image searchregion Ri to be accurately corrected depending on how the gradientdifference Δα, which is due to an error in relative distance of theimage search region Ri, is generated.

If the gradient difference Δα is generated between the reference roadsection on which the own vehicle 50 is travelling and the objective roadsection on which the preceding vehicle 60 is travelling, the error ofthe relative distance of the image detection point Pi relative to theown vehicle 50 probably changes depending on the position of thepreceding vehicle 60 in the captured image in the vertical direction.

From this viewpoint, the vehicle control apparatus is configured toobtain a value of the correction amount DA as a function of a value ofthe gradient difference Δα and a value of the position of the precedingvehicle 60 in the captured image in the vertical direction.

This configuration results in the gradient difference Δα and the errorof the relative distance of the image detection point Pi relative to theown vehicle 50 based on the position of the preceding vehicle 60 in thecaptured image in the vertical direction being reflected in thecorrection of the image detection point Pi. This therefore makes itpossible to more suitably correct the relative distance of the imagedetection point Pi relative to the own vehicle 50, thus more suitablycorrecting the image search region Ri.

Making the longitudinal length, i.e. the longitudinal range, of theimage search region Ri wide in correction of the image search region Ribeing closer to or father from the own vehicle 50 would result in theidentification determination condition being excessive likely to besatisfied, resulting in reduction of the accuracy of determining whetherthe radar-detected object is identical with the image-detected object.

From this viewpoint, the vehicle control apparatus is configured tocorrect the location of the image search region Ri to be closer to orfarther from the own vehicle 50, and correct the longitudinal range ofthe corrected image search region Ri in the distance direction to benarrower. This configuration prevents the radar search region Rr and thecorrected image search region CRi from being excessively overlapped witheach other, thus preventing the identification determination conditionfrom being excessively satisfied. This therefore prevents the accuracyof determining whether the radar-detected object is identical with theimage-detected object from being reduced.

The vehicle control apparatus is configured to obtain the gradientinformation about the reference road section on which the own vehicle 50is travelling and the gradient information on which the precedingvehicle 60 is travelling in accordance with

(1) The relative distance from the own vehicle 50 to the precedingvehicle 60

(2) The map information M including roads on which the own vehicle 50can travel

Specifically, the vehicle control apparatus is configured to

(1) Refer to the map information M about the road at the currentlocation of the own vehicle 50 to thereby obtain the gradientinformation about the reference road section on which the own vehicle 50is travelling

(2) Refer to the map information M about the road at the estimatedcurrent location of the preceding vehicle 60 to thereby obtain thegradient information on which the preceding vehicle 60 is travelling

This configuration therefore enables the relative gradient difference Δαbetween the reference road section on which the own vehicle 50 istravelling and the objective road section on which the preceding vehicle60 is travelling to be more accurately calculated.

Modifications

The present disclosure has been described with respect to the presentembodiment, however the present disclosure is not limited to the presentembodiment, and various types of modifications can be implemented.

The present embodiment is configured to determine whether theradar-detected object is identical with the image-detected object inaccordance with the radar search region Rr and the image search regionRi (see step S20), but the present disclosure is not limited thereto.

Specifically, the present disclosure can be configured to determinewhether the radar-detected object is identical with the image-detectedobject in accordance with the radar detection point Pr and the imagedetection point Pi (see, for example, steps S20 a to S20 d).

For example, in step S20, the ECU 10 can be configured to determinewhether the corrected image detection point CPi (see step S19) islocated within a predetermined distance range around the radar detectionpoint Pr, and determine whether the radar-detected object is identicalwith the image-detected object in accordance with the determinationresult of whether the corrected image detection point CPi is locatedwithin the predetermined distance range around the radar detection pointPr.

The present embodiment is configured to estimate, based on the relativedistance of the image detection point Pi relative to the reference pointO of the own vehicle 50, the current location of the preceding vehicle60 in calculation of the inclination angle α2 of the objective roadsection on which the preceding vehicle 60 is travelling, but the presentdisclosure is not limited to this configuration. Specifically, thepresent disclosure can be configured to estimate, based on the relativedistance of the radar detection point Pr relative to the reference pointO of the own vehicle 50, the current location of the preceding vehicle60.

The present embodiment is configured to correct, based on the calculatedrelative gradient difference Δα, the location of the image detectionpoint Pi, and correct, based on the corrected location of the imagedetection point Pi, the location of the image search region Ri in thedistance direction, but the present disclosure is not limited thereto.

Specifically, the present disclosure can be configured to correct, basedon the calculated relative gradient difference Δα, the location of theimage search region Ri in the distance direction directly withoutcorrecting the location of the image detection point Pi.

That is, the ECU 10 according to this modification is configured to

(1) Set a value of the correction amount DA in accordance with a valueof the preceding vehicle 60 in the captured image in the verticaldirection and a value of the relative gradient difference Δα

(2) Correct the image search region Ri in the distance direction basedon the value of the correction amount DA to thereby obtain the correctedimage search region CRi

The present disclosure can be configured to variably set the percentageby which the longitudinal range of the image search region Ri is to becorrected. For example, the present disclosure can be configured tovariable set the percentage depending on the correction amount DA. Forexample, the present disclosure can be configured to reduce thepercentage with an increase of the correction amount DA, making itpossible to prevent the identification determination condition frombeing satisfied excessively easily.

The present embodiment assumes that the fusion target object is apreceding vehicle 60, but the present disclosure can be configured todetect a bicycle or a pedestrian as a target object, such as a fusiontarget object.

The ECU 10 according to the present embodiment is applied to the PCSsystem 100, and is configured to improve the accuracy of determiningwhether a radar-detected object is identical with an image-detectedobject to thereby carry out an improved collision avoidance operationand/or an improved damage mitigation operation. The ECU 10 according tothe present embodiment can be applied to an adaptive cruise control(ACC) system that controls the own vehicle 50 to follow a precedingvehicle 60. This enables the adaptive cruise control of the own vehicle50 to be more accurately carried out.

The functions of one element in the present embodiment can bedistributed as plural elements, and the functions that plural elementshave can be combined into one element. At least part of the structure ofthe present embodiment can be replaced with a known structure having thesame function as the at least part of the structure of the presentembodiment. A part of the structure of the present embodiment can beeliminated.

All aspects included in the technological ideas specified by thelanguage employed by the claims constitute embodiments of the presentdisclosure.

While the illustrative embodiment of the present disclosure has beendescribed herein, the present disclosure is not limited to theembodiment described herein, but includes any and all embodiments havingmodifications, omissions, combinations (e.g., of aspects across variousembodiments), adaptations and/or alternations as would be appreciated bythose having ordinary skill in the art based on the present disclosure.The limitations in the claims are to be interpreted broadly based on thelanguage employed in the claims and not limited to examples described inthe present specification or during the prosecution of the application,which examples are to be construed as non-exclusive.

What is claimed is:
 1. An apparatus for controlling an own vehicle thatis travelling on a reference road section, the own vehicle including aradar device and an imaging device that are each configured to perform atarget-object detection operation, the apparatus comprising: a firstobtainer configured to obtain first location information about aradar-detected object in accordance with a result of the target-objectdetection operation performed by the radar device, the first locationinformation including a first distance of the radar-detected objectrelative to the own vehicle and a first azimuth of the radar-detectedobject relative to the own vehicle; a second obtainer configured toobtain second location information about an image-detected objectlocated on an objective road section based on a result of thetarget-object detection operation performed by the imaging device, thesecond location information including a second distance of theimage-detected object relative to the own vehicle and a second azimuthof the image-detected object relative to the own vehicle; a gradientcalculator configured to calculate a gradient difference between areference gradient of the reference road section and a target gradientof the objective road section; a corrector configured to correct, basedon the calculated gradient difference, the second location informationabout the image-detected object to thereby correct the second distanceof the image-detected object relative to the own vehicle; and adeterminer configured to determine whether the radar-detected object isidentical with the image-detected object in accordance with the firstlocation information about the radar-detected object and the correctedsecond location information about the image-detected object.
 2. Theapparatus according to claim 1, wherein: the imaging device isconfigured to capture an image of a region including the image-detectedobject as the target-object detection operation, the image having apredetermined height in a vertical direction thereof and a width in ahorizontal direction thereof; and the corrector is configured to: obtaina correction amount in accordance with the gradient difference and aposition of a predetermined point of the image-detected object in thecaptured image in the vertical direction; and correct the seconddistance of the image-detected object relative to the own vehicle inaccordance with the obtained correction amount.
 3. The apparatusaccording to claim 1, wherein: the first obtainer is configured toobtain, as the first location information, a first search region that:includes the first position of the radar-detected object; and has apredetermined distance range along a direction of the first distancerelative to the own vehicle and a predetermined azimuth range along adirection of the first azimuth relative to the own vehicle; the secondobtainer is configured to obtain, as the second location information, asecond search region that: includes the second position of theimage-detected object; and has a predetermined distance range along adirection of the second distance relative to the own vehicle and apredetermined azimuth range along a direction of the second azimuthrelative to the own vehicle; the corrector is configured to correct,based on the calculated gradient difference, a location of the secondsearch region in the direction of the second distance; and thedeterminer is configured to determine whether the radar-detected objectis identical with the image-detected object in accordance with the firstsearch region and the corrected second search region.
 4. The apparatusaccording to claim 3, wherein: the corrector is configured to: correctthe second search region to be closer to the own vehicle; and correctthe distance range of the second search region to be narrower upon thetarget gradient of the objective road section being positively greaterthan the reference gradient of the reference road section; and thedeterminer is configured to determine whether the first search region isat least partially overlapped with the corrected second search region tothereby determine whether the radar-detected object is identical withthe image-detected object.
 5. The apparatus according to claim 3,wherein: the corrector is configured to: correct the second searchregion to be farther from the own vehicle; and correct the distancerange of the second search region to be narrower upon the targetgradient of the objective road section being smaller than the referencegradient of the reference road section; and the determiner is configuredto determine whether the first search region is at least partiallyoverlapped with the corrected second search region to thereby determinewhether the radar-detected object is identical with the image-detectedobject.
 6. The apparatus according to claim 3, wherein: the imagingdevice is configured to capture an image of a region including theimage-detected object as the target-object detection operation, theimage having a predetermined height in a vertical direction thereof anda width in a horizontal direction thereof; and the corrector isconfigured to: obtain a correction amount in accordance with thegradient difference and a position of a predetermined point of theimage-detected object in the captured image in the vertical direction;and correct the location of the second search region in the direction ofthe second distance.
 7. The apparatus according to claim 1, wherein: thegradient calculator is configured to calculate the gradient differencebetween the reference gradient of the reference road section and thetarget gradient of the objective road section in accordance with: thesecond distance of the image-detected object relative to the ownvehicle; and map information including roads on which the own vehicle isenabled to travel.
 8. The apparatus according to claim 2, furthercomprising: a storage storing relationship information that includes: arelationship between: values of the gradient difference; values of theposition of the predetermined point of the image-detected object in thecaptured image in the vertical direction; and values of the correctionamount, wherein the corrector is configured to: extract, from therelationship information, a value of the correction amount, theextracted value of the correction amount matching with a present valueof the gradient difference and a present value of the position of thepredetermined point of the image-detected object in the captured imagein the vertical direction; and correct the second distance of theimage-detected object relative to the own vehicle in accordance with theextracted value of the correction amount.
 9. A method of controlling,using a computer, an own vehicle that is travelling on a reference roadsection, the own vehicle including a radar device and an imaging devicethat are each configured to perform a target-object detection operation,the method being configured to cause the computer to execute the stepsof: obtaining first location information about a radar-detected objectin accordance with a result of the target-object detection operationperformed by the radar device, the first location information includinga first distance of the radar-detected object relative to the ownvehicle and a first azimuth of the radar-detected object relative to theown vehicle; obtaining second location information about animage-detected object located on an objective road section based on aresult of the target-object detection operation performed by the imagingdevice, the second location information including a second distance ofthe image-detected object relative to the own vehicle and a secondazimuth of the image-detected object relative to the own vehicle;calculating a gradient difference between a reference gradient of thereference road section and a target gradient of the objective roadsection; correcting, based on the calculated gradient difference, thesecond location information about the image-detected object to therebycorrect the second distance of the image-detected object relative to theown vehicle; and determining whether the radar-detected object isidentical with the image-detected object in accordance with the firstlocation information about the radar-detected object and the correctedsecond location information about the image-detected object.